Title Advancing chemical and drug safety testing using single-cell RNA-sequencing Project Summary Drug and chemical safety evaluations represent a significant challenge for the protection of human health. For example, adverse drug responses required millions of hospitalizations and caused ~100,000 deaths in the US while chemical safety evaluations are onerous tasks taking years to complete. More recently, gene expression profiling has been used, providing a more comprehensive understanding of the mode of action (MOA), as well as reducing the time, cost, and number of animals required for testing. In addition, dose-response modeling of transcriptomic changes has provided point of departure (POD) estimates that are predictive of long-term apical responses such as hepatotoxicity and carcinogenesis. Despite these advances, gene expression profiling relies on bulk RNA-sequencing of heterogeneous tissue, which is unable to distinguish cell-specific adverse effects within whole tissue. The ability to decipher cell-specific effects associated with adverse responses within a tissue would significantly improve (i) MOA elucidation, (ii) the identification of sensitive cell types and (ii) predictions of human toxicity relevance, especially when determining initial doses in clinical trials. Single-cell RNA-sequencing (scRNAseq) circumvents the limitations of bulk RNA-sequencing. However, tools for assessing dose-dependent effects using scRNAseq data do not exist. This proposal will develop a pipeline for the analysis of scRNAseq dose response chemical and drug safety data. This will include experimental criteria (throughput and read depth) required to ensure reproducibility. We will use the well-characterized non-genotoxic hepatocarcinogen, 2,3,7,8- tetrachlorodibenzo-p-dioxin (TCDD) as our test chemical. Comprehensive phenotypic and bulk RNA-seq data is widely available for TCDD enabling phenotypic anchoring and detailed comparisons. Specific Aim 1 will demonstrate the identification of the dose-dependent emergence of new cell types and states using scRNAseq data while Aim 2 will adapt existing computational dose-response modelling tools to determine cell- and gene- specific PODs that will be anchored to apical endpoints. This will be the first application of scRNAseq to investigate dose-dependent response to an exogenous agent, thus establishing the foundation of scRNAseq in pharmacology, toxicology and drug development.